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<div><a href="../../index.html">Home</a> &gt;  <a href="../index.html">CO4OI</a> &gt; <a href="index.html">operators</a> &gt; analop3dfft.m</div>

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<h1>analop3dfft
</h1>

<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
<div class="box"><strong></strong></div>

<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
<div class="box"><strong>function [ y ] = analop3dfft( Tx, n, m, maskB) </strong></div>

<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
<div class="fragment"><pre class="comment">

 analop3dfft computes 2D-Fourier Transform along the 3 dimensions of cubic
 tensor T and evaluates it in frequences open in maskB

 INPUT

   - Tx: Input tensor
   - [n, m] dimension of the underlying signal (i.e. Tx \in R^(N*N*N)
   where N=n*m
   - maskB mask indicating open frequencies</pre></div>

<!-- crossreference -->
<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
This function calls:
<ul style="list-style-image:url(../../matlabicon.gif)">
<li><a href="analop_fft_6d.html" class="code" title="function T = analop_fft_6d(T, n, m)">analop_fft_6d</a>	</li></ul>
This function is called by:
<ul style="list-style-image:url(../../matlabicon.gif)">
</ul>
<!-- crossreference -->



<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
<div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function [ y ] = analop3dfft( Tx, n, m, maskB)</a>
0002 <span class="comment">%</span>
0003 <span class="comment">%</span>
0004 <span class="comment">% analop3dfft computes 2D-Fourier Transform along the 3 dimensions of cubic</span>
0005 <span class="comment">% tensor T and evaluates it in frequences open in maskB</span>
0006 <span class="comment">%</span>
0007 <span class="comment">% INPUT</span>
0008 <span class="comment">%</span>
0009 <span class="comment">%   - Tx: Input tensor</span>
0010 <span class="comment">%   - [n, m] dimension of the underlying signal (i.e. Tx \in R^(N*N*N)</span>
0011 <span class="comment">%   where N=n*m</span>
0012 <span class="comment">%   - maskB mask indicating open frequencies</span>
0013 <span class="comment">%</span>
0014 
0015 
0016 N=n*m;
0017 Tx=reshape(Tx,N,N,N);
0018 
0019 
0020 y0=<a href="analop_fft_6d.html" class="code" title="function T = analop_fft_6d(T, n, m)">analop_fft_6d</a>(Tx,n,m);
0021 
0022 
0023 maskB=logical(maskB);
0024  
0025 
0026 y=y0(maskB);
0027 
0028 
0029 <span class="keyword">end</span>
0030</pre></div>
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